patell: Patell's parametric test (1976).

In irudnyts/estudy2: An Implementation of Parametric and Nonparametric Event Study

Patell's parametric test (1976).

Description

An event study parametric test described in Patell 1976.

Usage

patell(list_of_returns, event_start, event_end)

Arguments

list_of_returns	a list of objects of S3 class returns, each element of which is treated as a security.
event_start	an object of Date class giving the first date of the event period.
event_end	an object of Date class giving the last date of the event period.

Details

Performs a parametric test for event study, which is described in Patell 1976, which is called standardized-residuals method in Boehmer 1991. Test's assumptions are a cross-sectional independence and an insignificance of an event-induced variance. The standardization smooths the effect of the event-induced variance comparing to Brown and Warner tests. Also standardization incorporates the situation, when a highly volatile security dominates the test. The test examines the hypothesis whether the theoretical cross-sectional expected value for a given day is equal to zero. It calculates statistics even if event window and estimation period are overlapped (intersect). The critical values are standard normal. The significance levels of α are 0.1, 0.05, and 0.01 (marked respectively by *, **, and ***).

Value

A data frame of the following columns:

• date: a calendar date

• weekday: a day of the week

• percentage: a share of non-missing observations for a given day

• mean: an average abnormal return

• pt_stat: a Patell's test statistic

• pt_signif: a significance of the statistic

References

• Patell J.M. Corporate forecasts of earnings per share and stock price behavior: empirical tests. Journal of Accounting Research, 14(2):246- 276, 1976.

• Boehmer E., Musumeci J., Poulsen A.B. Event-study methodology under conditions of event-induced variance. Journal of Financial Economics, 30(2):253-272, 1991.

See Also

parametric_tests, brown_warner_1980, brown_warner_1985, t_test, and boehmer, and lamb.

Examples

## Not run: 
library("magrittr")
rates_indx <- get_prices_from_tickers("^GSPC",
                                      start = as.Date("2019-04-01"),
                                      end = as.Date("2020-04-01"),
                                      quote = "Close",
                                      retclass = "zoo") %>%
    get_rates_from_prices(quote = "Close",
                          multi_day = TRUE,
                          compounding = "continuous")
tickers <- c("AMZN", "ZM", "UBER", "NFLX", "SHOP", "FB", "UPWK")
get_prices_from_tickers(tickers,
                        start = as.Date("2019-04-01"),
                        end = as.Date("2020-04-01"),
                        quote = "Close",
                        retclass = "zoo") %>%
    get_rates_from_prices(quote = "Close",
                          multi_day = TRUE,
                          compounding = "continuous") %>%
    apply_market_model(regressor = rates_indx,
                       same_regressor_for_all = TRUE,
                       market_model = "sim",
                       estimation_method = "ols",
                       estimation_start = as.Date("2019-04-01"),
                       estimation_end = as.Date("2020-03-13")) %>%
    patell(event_start = as.Date("2020-03-16"),
           event_end = as.Date("2020-03-20"))

## End(Not run)
## The result of the code above is equivalent to:
data(securities_returns)
patell(list_of_returns = securities_returns,
       event_start =  as.Date("2020-03-16"),
       event_end = as.Date("2020-03-20"))

irudnyts/estudy2 documentation built on April 21, 2022, 10:50 p.m.